The impact of the Green Industry paradigm on a business perspective - LP2 (884 LP) 
Sustainability Readiness: Navigating Industry Standards and Implementation (1035 LP) 
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Explore EIT Manufacturing Academy’s extensive training catalogue, offering a diverse range of learning activities including digital modules, live sessions, blended training, and hands-on practice. Whether you prefer flexible online learning or interactive in-person experiences, browse our comprehensive list where featured selections are highlighted for your convenience. Discover your path to success with us today!
PyBullet for manipulator simulation
Introduction to the PyBullet Python module for robotics simulation.
Cost Models of Additive Manufacturing
This nuggets provides information on the cost structure and cost drivers in Additive Manufacturing.
What can go wrong in ROS applications?
Did you know that ROS applications may be vulnerable to cyberattacks?
Model Predictive Control - The main ingredients
This nuggets will present and formulate the main ingredients one need to implement a Model Predictive Controller.
- Quiz1
Reactive Collision Avoidance: Dynamic Window Approach
The purpose of this nugget is to provide an overview of what the Dynamic Window Approach is, and how it is used in autonomous navigation.
ROS Communication - Communication establishment
Introduction to the Communication Establishment Protocols in used in the Robot Operating System (ROS)
CPS&IoT: Software Engineering Dependability
This digital module is designed to provide an introduction to the principles and practices of software engineering for dependable Cyber-Physical Systems (CPS) and Internet of Things (IoT) applications.
Machine Vision for Quality Control - Introduction
The "Machine Vision for Quality Control - Introduction" learning nugget provides an introductory exploration of the integration of machine vision technology in quality control processes. This learning experience will equip participants with an understanding of the fundamental concepts, advantages, and potential obstacles associated with machine vision systems. Learners will gain insights into the multifaceted landscape of machine vision and its pivotal role in enhancing product quality.